Daniel Kifer

Professor of Computer Science & Engineering

Daniel Kifer

Publication Tags

Learning Convolutional Neural Networks Soil Moisture Neural Networks Prediction Semantics Crime Statistics Simulation Method Moisture Sampling Pixels Community Pressure Opinion High Dimensional Carbon Atom Laboratory Acoustic Waves Backpropagation Offense Prolongation Flow Convolution

Most Recent Papers


Yuxin Wang, Zeyu DIng, Yingtai Xiao, Daniel Kifer, Danfeng Zhang, 2021, on p. 393-411

Physics-informed deep learning for prediction of CO<sub>2</sub> storage site response

Parisa Shokouhi, Vikas Kumar, Sumedha Prathipati, Seyyed A. Hosseini, Clyde Lee Giles, Daniel Kifer, 2021, Journal of Contaminant Hydrology

Deep Learning Can Predict Laboratory Quakes From Active Source Seismic Data

Parisa Shokouhi, Vrushali Girkar, Jacques Rivière, Srisharan Shreedharan, Chris Marone, C. Lee Giles, Daniel Kifer, 2021, Geophysical Research Letters


Shivansh Rao, Vikas Kumar, Daniel Kifer, C. Lee Giles, Ankur Mali, 2021, on p. 3701-3710

An Empirical Analysis of Recurrent Learning Algorithms in Neural Lossy Image Compression Systems

Ankur Mali, Alexander G. Ororbia, Dan Kifer, C. Lee Giles, 2021, on p. 356

Optimizing fitness-for-use of differentially private linear Queries

Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer, 2021, Proceedings of the VLDB Endowment on p. 1730-1742

Network Spillovers and Neighborhood Crime

Corina Graif, Brittany N. Freelin, Yu Hsuan Kuo, Hongjian Wang, Zhenhui Li, Daniel Kifer, 2021, Justice Quarterly on p. 344-374

Evaluating the Potential and Challenges of an Uncertainty Quantification Method for Long Short-Term Memory Models for Soil Moisture Predictions

Kuai Fang, Daniel Kifer, Kathryn Lawson, Chaopeng Shen, 2020, Water Resources Research

CheckDP: An Automated and Integrated Approach for Proving Differential Privacy or Finding Precise Counterexamples

Yuxin Wang, Zeyu Ding, Daniel Kifer, Danfeng Zhang, 2020, on p. 919-938

Continual Learning of Recurrent Neural Networks by Locally Aligning Distributed Representations

Alexander Ororbia, Ankur Mali, C. Lee Giles, Daniel Kifer, 2020, IEEE Transactions on Neural Networks and Learning Systems on p. 4267-4278

Most-Cited Papers


Daniel Kifer, Ashwin Machanavajjhala, 2014, ACM Transactions on Database Systems

Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network

Kuai Fang, Chaopeng Shen, Daniel Kifer, Xiao Yang, 2017, Geophysical Research Letters on p. 11,030-11,039

Learning to read irregular text with attention mechanisms

Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles, 2017, on p. 3280-3286

HESS opinions: Incubating deep-learning-powered hydrologic science advances as a community

Chaopeng Shen, Eric Laloy, Amin Elshorbagy, Adrian Albert, Jerad Bales, Fi John Chang, Sangram Ganguly, Kuo Lin Hsu, Daniel Kifer, Zheng Fang, Kuai Fang, Dongfeng Li, Xiaodong Li, Wen Ping Tsai, 2018, Hydrology and Earth System Sciences on p. 5639-5656

Crime rate inference with big data

Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li, 2016, on p. 635-644

Learning to extract semantic structure from documents using multimodal fully convolutional neural networks

Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, C. Lee Giles, 2017, on p. 4342-4351

A rigorous and customizable framework for privacy

Daniel Kifer, Ashwin Machanavajjhala, 2012, on p. 77-88

Multi-scale FCN with cascaded instance aware segmentation for arbitrary oriented word spotting in the wild

Dafang He, Xiao Yang, Chen Liang, Zihan Zhou, Alex G. Ororbia, Daniel Kifer, C. Lee Giles, 2017, on p. 474-483

Multi-Scale Multi-Task FCN for Semantic Page Segmentation and Table Detection

Dafang He, Scott Cohen, Brian Price, Daniel Kifer, C. Lee Giles, 2017, on p. 254-261

Private convex empirical risk minimization and high-dimensional regression

Daniel Kifer, Adam Smith, Abhradeep Thakurta, 2012, Journal of Machine Learning Research on p. 25.1-25.40